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BACKGROUND: Previous studies suggest that Supplemental Nutrition Assistance Program (SNAP) participants purchase less produce than nonparticipants. Whether this is due to buying smaller amounts or to being less likely to buy any produce is unclear. Purchase patterns may also differ over the monthly distribution cycle. OBJECTIVE: To examine differences in the likelihood and amounts of fruits and vegetables purchased between SNAP household compared with nonparticipant households and to determine differences in produce purchases among SNAP households at different time points in the monthly distribution cycle. DESIGN: Cross-sectional. PARTICIPANTS/SETTING: Data from 4708 households in the National Household Food Acquisition and Purchase Survey (April 2012 to January 2013). Participants recorded all foods acquired over 7 days. MAIN OUTCOME MEASURES: Fruits and vegetables acquired over a 7-day period. STATISTICAL ANALYSES PERFORMED: Weighted logistic and linear regression models adjusting for household and primary respondent characteristics were used to compare odds of purchasing fruits and vegetables and amounts purchased across 3 categories: SNAP participants, SNAP-eligible nonparticipants, and ineligible nonparticipants. SNAP participants were further subdivided according to weeks since last receiving benefits. RESULTS: In adjusted analyses, SNAP participants and nonparticipants were similarly likely to purchase fruits and vegetables. However, SNAP households within a week of receiving benefits were more likely than SNAP households later in the benefit cycle to buy fruit overall, especially frozen or canned fruit, and vegetables overall, including fresh, frozen or canned, starchy, and nonstarchy vegetables (fruit odds ratio [OR] 1.68, 95% confidence interval [CI] 1.12, 2.53; vegetable OR 1.63, 95% CI 1.04, 2.55 vs households in middle of cycle). In contrast, those in the last week of the benefit cycle were less likely to purchase fruit, especially fresh fruit, and vegetables, especially fresh and nonstarchy vegetables (fruit OR 0.58, 95% CI 0.35, 0.94; vegetable OR 0.58, 95% CI 0.42, 0.79 vs. households in middle of cycle), and when they bought vegetables, they bought significantly less. CONCLUSION: Considering all SNAP households together at different points in their distribution cycle masks substantial declines in purchasing fruits and vegetables over the monthly cycle.

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OBJECTIVE: Compare saturated fat, sugar, and sodium in the US Department of Agriculture sample menu with a version in which menu items were replaced with comparable ultra-processed foods. DESIGN AND SETTING: The authors modified 7 days of a US Department of Agriculture sample menu providing approximately 2,000 kcal/d by replacing foods with comparable ultra-processed alternatives and then visited 2 chain supermarkets in San Luis Obispo, CA (August, 2016) to locate shopping list items for the 2 menu versions. Product-specific bar codes were entered into an application for recording dietary intake and analyzing nutrient content. VARIABLES MEASURED/ANALYSIS: Paired t tests (with Bonferroni correction, α = .003) were performed to compare the menus' percent energy from saturated fat and sugar, and energy and sodium content. RESULTS: Mean energy was lower (1,618 vs 1,892 kcal/d; P = .002) whereas percent energy from sugar (24.9% vs 21.4%; P ≤ .001) and sodium content (2,784 vs 2,101 mg/d; P = .001) were higher in the ultra-processed vs original menu. In secondary analyses, mean cost of the ultra-processed version exceeded that of the original menu by $36.87. CONCLUSIONS AND IMPLICATIONS: In a sample menu developed to meet US Dietary Guidelines, substituting items with ultra-processed foods provided fewer calories but more sugar and sodium. Distinguishing ultra-processed from less processed foods may help consumers make healthier choices when using MyPlate tools, particularly in a food environment that presents a wide range of alternatives.

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INTRODUCTION: University campuses offer an opportunity to study the extent to which modifying the food environment influences eating, but in-depth characterizations of campus food environments are needed to identify potential targets for intervention. The objective of this project was to describe the availability, accessibility, and quality of healthful food choices in dining venues and food stores at or near a public, 4-year university in California. METHODS: Trained assessors used the Nutrition Environment Measures Survey for campus dining (NEMS-CD) to evaluate all 18 campus dining venues, and NEMS for stores (NEMS-S) to evaluate 2 on-campus and 37 off-campus food stores. We calculated prevalence of healthful and unhealthful constructs (eg, availability of selected food items, presence of signage encouraging healthful eating, pricing options that encourage healthful eating), based on the NEMS and compared scores across different types of venues. RESULTS: NEMS-CD scores ranged from 4 to 47 (mean [SD], 26.0 [14.4]) out of a possible maximum score of 97; 12% of entrées and 36% of main dish salads served in these venues were classified as healthful. NEMS-S score for the 2 on-campus food stores (24 for both) was intermediate between off-campus convenience stores (mean [SD], 12.0 [5.3]) and grocery/supermarket stores (mean [SD], 31.1 [10.0]), with a possible maximum score of 54. CONCLUSION: Standardized environmental evaluation provides insights into both positive and negative aspects of campus community food venues. Environmental assessment identifies potential targets for modification and baseline data for designing and implementing action-oriented research aimed at improving the campus food environment's support of healthful food choices for college students.

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Parental investment decisions guide parental actions regarding children's productive work and are shaped by ecological context. Urban ecology enhances long-term payoffs to investment in human capital, increasing opportunity costs for work performed by children, and decreased workload should result. Using an embodied capital framework, self-reported data on urban and rural Indo-Fijian children's work activities are compared. Results show higher workloads for older children, rural children, and girls. High scholastic achievement is associated with lower workloads for girls, but not boys. This pattern is interpreted as daughter-biased investment in the context of urbanization.

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Health research has shown that overweight and obesity in children and adults are becoming significant public health problems in the developing world. Evidence suggests that this phenomenon is more marked in urban than rural areas and may be associated with modernization. However, the underlying reasons for this nutrition transition remain unclear. Dietary shifts, often in conjunction with income and time constraints in urban environments, may entail a greater reliance on more convenient sugar and fat-dense food. Also, the necessity of labor-intensive agricultural work to meet rural subsistence needs is supplanted in urban environments by sedentary work. This paper extends the application of human behavioral ecology theory into the realm of international development and policy by applying Kaplan's embodied capital theory to explore differences in food habits and nutritional status of Indo-Fijian children within the context of urbanization. Urban high-embodied-capital women demonstrate higher rates of wage-earning employment than urban low-embodied-capital or rural women. Findings indicate that urban high-embodied-capital households spend significantly more on food purchases, purchase a greater proportion of processed foods, and have children with higher body mass indexes (BMI) than do urban low-embodied-capital or rural households. This suggests that urban high-embodied-capital mothers, who tend to be employed, may be making trade-offs between income and food choices.